Home » date » 2010 » Apr » 29 »

The total generation of electricity by the U.S. electric industry

*Unverified author*

R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Thu, 29 Apr 2010 12:57:20 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Apr/29/t12725459061xpk655z9xsc1ni.htm/, Retrieved Thu, 29 Apr 2010 14:58:28 +0200

BibTeX entries for LaTeX users:

@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Apr/29/t12725459061xpk655z9xsc1ni.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W21

Dataseries X:

» Textbox « » Textfile « » CSV «

227.86 198.24 194.97 184.88 196.79 205.36 226.72 226.05 202.50 194.79 192.43 219.25 217.47 192.34 196.83 186.07 197.31 215.02 242.67 225.17 206.69 197.75 196.43 213.55 222.75 194.03 201.85 189.50 206.07 225.59 247.91 247.64 213.01 203.01 200.26 220.50 237.90 216.94 214.01 196.00 208.37 232.75 257.46 267.69 220.18 210.61 209.59 232.75 232.75 219.82 226.74 208.04 220.12 235.69 257.05 258.69 227.15 219.91 219.30 259.04 237.29 212.88 226.03 211.07 222.91 249.18 266.38 268.53 238.02 224.69 213.75 237.43 248.46 210.82 221.40 209.00 234.37 248.43 271.98 268.11 233.88 223.43 221.38 233.76 243.97 217.76 224.66 210.84 220.35 236.84 266.15 255.20 234.76 221.29 221.26 244.13 245.78 224.62 234.80 211.37 222.39 249.63 282.29 279.13 236.60 223.62 225.86 246.41 261.70 225.01 231.54 214.82 227.70 263.86 278.15 274.64 237.66 227.97 224.75 242.91 253.08 228.13 233.68 217.38 236.38 256.08 292.83 304.71 etc...

Output produced by software:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.109327	1.2982	0.098171
2	-0.23166	-2.7508	0.003363
3	-0.512283	-6.083	0
4	-0.307956	-3.6568	0.00018
5	0.313155	3.7185	0.000144
6	0.241754	2.8707	0.002364
7	0.33769	4.0098	4.9e-05
8	-0.292026	-3.4676	0.000348
9	-0.480184	-5.7019	0
10	-0.201833	-2.3966	0.008929
11	0.116051	1.378	0.085188
12	0.823177	9.7747	0
13	0.147737	1.7543	0.040778
14	-0.205215	-2.4368	0.008032
15	-0.473794	-5.626	0
16	-0.271266	-3.2211	0.000793
17	0.252069	2.9931	0.001631
18	0.211693	2.5137	0.006535
19	0.31943	3.793	0.00011
20	-0.238499	-2.832	0.002652
21	-0.435306	-5.169	0
22	-0.195949	-2.3268	0.010701
23	0.113701	1.3501	0.08957
24	0.71362	8.4738	0
25	0.14799	1.7573	0.04052
26	-0.172919	-2.0533	0.020946
27	-0.426108	-5.0598	1e-06
28	-0.272735	-3.2385	0.000749
29	0.258943	3.0748	0.001265
30	0.168516	2.001	0.023655
31	0.294853	3.5012	0.00031
32	-0.202812	-2.4083	0.00866
33	-0.402411	-4.7784	2e-06
34	-0.170665	-2.0265	0.022298
35	0.104531	1.2412	0.10829
36	0.645899	7.6696	0
37	0.114378	1.3582	0.088291
38	-0.176669	-2.0978	0.018852
39	-0.328954	-3.9061	7.2e-05
40	-0.25326	-3.0073	0.001561
41	0.225566	2.6785	0.004138
42	0.127673	1.516	0.065875
43	0.249728	2.9654	0.001776
44	-0.162573	-1.9304	0.02778
45	-0.340939	-4.0484	4.2e-05
46	-0.147893	-1.7561	0.040619
47	0.082514	0.9798	0.164432
48	0.564411	6.702	0

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.109327	1.2982	0.098171
2	-0.246559	-2.9277	0.001991
3	-0.48897	-5.8062	0
4	-0.408045	-4.8453	2e-06
5	0.101259	1.2024	0.115615
6	-0.192179	-2.282	0.011993
7	0.188323	2.2362	0.013454
8	-0.262261	-3.1142	0.001117
9	-0.399969	-4.7494	2e-06
10	-0.366779	-4.3553	1.3e-05
11	-0.43582	-5.1751	0
12	0.425948	5.0579	1e-06
13	0.029548	0.3509	0.363109
14	0.010147	0.1205	0.452133
15	0.108351	1.2866	0.100172
16	0.207656	2.4658	0.007436
17	0.007409	0.088	0.465008
18	-0.044587	-0.5294	0.298664
19	-0.027259	-0.3237	0.37333
20	0.01258	0.1494	0.440734
21	-0.061557	-0.731	0.233011
22	-0.09946	-1.181	0.119791
23	-0.089294	-1.0603	0.145408
24	0.061962	0.7358	0.23155
25	-0.073485	-0.8726	0.192188
26	-0.046459	-0.5517	0.291024
27	0.018509	0.2198	0.413177
28	-0.078519	-0.9324	0.176372
29	0.157137	1.8659	0.032067
30	-0.040385	-0.4795	0.316148
31	0.000705	0.0084	0.496665
32	0.028866	0.3428	0.366142
33	-0.011361	-0.1349	0.446441
34	-0.024493	-0.2908	0.3858
35	-3.2e-05	-4e-04	0.49985
36	0.030836	0.3662	0.357396
37	-0.07676	-0.9115	0.181801
38	-0.121882	-1.4473	0.07502
39	0.13191	1.5663	0.059754
40	0.032221	0.3826	0.351296
41	-0.053542	-0.6358	0.262976
42	-0.042918	-0.5096	0.305557
43	-0.035618	-0.4229	0.336491
44	0.005022	0.0596	0.476264
45	-0.001822	-0.0216	0.491387
46	-0.069742	-0.8281	0.204496
47	-0.035801	-0.4251	0.335703
48	0.007787	0.0925	0.463229

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Apr/29/t12725459061xpk655z9xsc1ni/1bpam1272545838.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t12725459061xpk655z9xsc1ni/1bpam1272545838.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t12725459061xpk655z9xsc1ni/2mhs71272545838.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t12725459061xpk655z9xsc1ni/2mhs71272545838.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

R code (references can be found in the software module):

if (par1 == 'Default') {

par1 = 10*log10(length(x))

} else {

par1 <- as.numeric(par1)

}

par2 <- as.numeric(par2)

par3 <- as.numeric(par3)

par4 <- as.numeric(par4)

par5 <- as.numeric(par5)

if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'

par7 <- as.numeric(par7)

if (par2 == 0) {

x <- log(x)

} else {

x <- (x ^ par2 - 1) / par2

}

if (par3 > 0) x <- diff(x,lag=1,difference=par3)

if (par4 > 0) x <- diff(x,lag=par5,difference=par4)

bitmap(file='pic1.png')

racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))

dev.off()

bitmap(file='pic2.png')

rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')

dev.off()

(myacf <- c(racf$acf))

(mypacf <- c(rpacf$acf))

lengthx <- length(x)

sqrtn <- sqrt(lengthx)

load(file='createtable')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Autocorrelation Function',4,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,'Time lag k',header=TRUE)

a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)

a<-table.element(a,'T-STAT',header=TRUE)

a<-table.element(a,'P-value',header=TRUE)

a<-table.row.end(a)

for (i in 2:(par1+1)) {

a<-table.row.start(a)

a<-table.element(a,i-1,header=TRUE)

a<-table.element(a,round(myacf[i],6))

mytstat <- myacf[i]*sqrtn

a<-table.element(a,round(mytstat,4))

a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable.tab')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,'Time lag k',header=TRUE)

a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)

a<-table.element(a,'T-STAT',header=TRUE)

a<-table.element(a,'P-value',header=TRUE)

a<-table.row.end(a)

for (i in 1:par1) {

a<-table.row.start(a)

a<-table.element(a,i,header=TRUE)

a<-table.element(a,round(mypacf[i],6))

mytstat <- mypacf[i]*sqrtn

a<-table.element(a,round(mytstat,4))

a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable1.tab')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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